Evidence and Narrative in Research: From Osman & Abramson to Thermal Comfort Studies
DESN2003: Research for Innovation, Week Six
2025-03-06
1: From Osman & Abramson to Thermal Comfort Studies: Evidence and Narrative in Research
A Data-Driven Qualitative Review in Architectural Research
2: What makes a story credible?
3: Let’s open with some ideas from Osman & Abramson
- Osman’s Idea:
- Evidence is not self-explanatory.
- Facts become “evidence” when selectively assembled into a narrative.
- Abramson’s Contribution:
- Advocates for an “undetermined history.”
- Emphasizes embracing ambiguity, accident, and counter-narratives.
Leverage these ideas as the thread that stitches our session together.
4: Session Overview & Objectives
- Our Focus:
- Use Osman & Abramson as theoretical anchors to examine research narratives.
- Case study: “A Data-Driven Qualitative Review of Thermal Comfort Studies.”
- Learning Outcomes:
- Understand roles of primary vs. secondary data.
- Recognize how narrative is constructed—and what is omitted.
- Develop strategies for critical, reflexive evidence gathering.
5: Introduction & Context Setting
- Exploration:
- How evidence and narrative work together in research.
- Our case study is the provided draft on thermal comfort studies.
- Focus:
- Examining how the draft uses different data types to build its narrative.
6: Dissecting the Draft’s Methodology
- Data Collection:
- Primary Data: Field measurements, surveys, direct observations.
- Secondary Data: Established databases (e.g., ASHRAE, Chinese TCDB) and literature.
- Systematic Approach:
- Literature screening, numerical evaluation criteria (scores 0–3).
- Mapping personal (age, gender, BMI) and contextual parameters.
This method exemplifies how facts are mobilized into evidence, as Osman suggests.
-3 (cold) to 0 (neutral) to +3 (hot)
7: Mapping between perception and numbers: A Quantitative Review
What benefits and drawbacks do you see in using numerical scoring to convert raw data into a narrative?
8: Primary vs. Secondary Data Sources
- Primary Data:
- Direct measurements (e.g., temperature, humidity).
- First-hand surveys and observations.
- Secondary Data:
- Data from previous studies and databases.
- Provides context and broadens scope.
The draft combines both to create a layered narrative.
9: How Did We Do This in Our Manuscript?
- Leveraging Secondary Data:
- Utilized established thermal comfort databases (ASHRAE & Chinese TCDB) as our primary sources.
- Compiled 88+ articles to form our evidence base.
- Systematic Data Evaluation:
- Applied a numerical scoring system (0–3) to assess personal, contextual, and PMV parameters.
- Enabled structured comparison and identification of gaps across studies.
- Constructing the Narrative:
- Integrated diverse data points to build a coherent story that supports our hypothesis.
- Demonstrated how selection and framing of secondary data can drive new insights.
- Testament to Methodology:
- Our approach shows that robust secondary data can be effectively leveraged.
- Aligns with Osman’s and Abramson’s ideas on how evidence is reinterpreted into a narrative.
10: Critically Assessing Our Data Setup
- Maintain Critical Awareness:
- Triangulation: Validate findings by comparing multiple sources.
- Reflexivity: Regularly question data selection and categorization.
- Iterative Review: Continuously refine data collection and narrative as new evidence emerges.
- Draft’s Limitations:
- Inconsistent classifications and mapping issues.
- Underrepresentation of certain demographics.
- Future Enhancements:
- Develop standardized classification/predictive frameworks.
- Incorporate mixed-method approaches.
This process embodies the critical reflection championed by Osman and Abramson.
11: How can we ensure our data-driven narratives remain robust and adaptable as new evidence emerges?
12: Conclusion & Key Takeaways
- Summary:
- Evidence transforms into narrative through careful selection and interpretation.
- Our case study demonstrates both the potential and limitations in this process.
- Key Takeaways:
- Balance rigorous data collection with reflexive narrative construction.
- Be aware of what is included—and omitted—to strengthen research credibility.
- Osman and Abramson remind us to remain open to alternative interpretations.
Final Reflection:
“As researchers, how do we balance the rigor of data collection with the interpretive nature of narrative construction?”
13: Thank You & Q&A
Questions & Discussion?